Role of water in metal catalyst performance for ketone hydrogenation: a joint experimental and theoretical study on levulinic acid conversion into gamma-valerolactone

While Ru is a poor hydrogenation catalyst compared to Pt or Pd in the gas phase, it is efficient under aqueous phase conditions in the hydrogenation of ketones such as the conversion of levulinic acid into gamma-valerolactone. Combining DFT calculations and experiments, we demonstrate that water is responsible for the enhanced reactivity of Ru under those conditions

In situ X-ray Diffraction Computed Tomography studies examining the thermal and chemical stabilities of working Ba0.5Sr0.5Co0.8Fe0.2O3-δ membranes during oxidative coupling of methane

In this study we present the results from two in situ X-ray diffraction computed tomography experiments of catalytic membrane reactors (CMRs) using Ba0.5Sr0.5Co0.8Fe0.2O3−δ (BSCF) hollow fibre membranes and Na-Mn-W/SiO2 catalyst during the oxidative coupling of methane (OCM) reaction. The negative impact of CO2, when added to the inlet gas stream, is seen to be mainly related to the C2+ yield, while no evidence of carbonate phase(s) formation is found during the OCM experiments. The main degradation mechanism of the CMR is suggested to be primarily associated with the solid-state evolution of the BSCF phase rather than the presence of CO2. Specifically, in situ XRD-CT and post-mortem SEM/EDX measurements revealed a collapse of the cubic BSCF phase, formation of secondary phases, which include needle-like structures and hexagonal Ba6Co4O12, and formation of a BaWO4 layer, the latter being a result of chemical interaction between the membrane and catalyst materials at high temperatures

Type I interferon responses of common carp strains with different levels of resistance to koi herpesvirus disease during infection with CyHV-3 or SVCV

Carp from breeding strains with different genetic background present diverse levels of resistance to viral pathogens. Carp strains of Asian origin, currently being treated as Cyprinus rubrofuscus L., especially Amur wild carp (AS), were proven to be more resistant to koi herpesvirus disease (KHVD; caused by cyprinid herpesvirus 3, CyHV-3) than strains originating from Europe and belonging to Cyprinus carpio L., like the Prerov scale carp (PS) or koi carp from a breed in the Czech Republic. We hypothesised that it can be associated with a higher magnitude of type I interferon (IFN) response as a first line of innate defence mechanisms against viral infections. To evaluate this hypothesis, four strains of common carp (AS, Rop, PS and koi) were challenged using two viral infection models: Rhabdovirus SVCV (spring viremia of carp virus) and alloherpesvirus CyHV-3. The infection with SVCV induced a low mortality rate and the most resistant was the Rop strain (no mortalities), whereas the PS strain was the most susceptible (survival rate of 78%). During CyHV-3 infection, Rop and AS strains performed better (survival rates of 78% and 53%, respectively) than PS and koi strains (survival rates of 35% and 10%, respectively). The evaluation of virus loads and virus replication showed significant differences between the carp strains, which correlated with the mortality rate. The evaluation of type I IFN responses showed that there were fundamental differences between the virus infection models. While responses to the SVCV were high, the CyHV-3 generally induced low responses. Furthermore, the results demonstrated that the magnitude of type I IFN responses did not correlate with a higher resistance in infected carp. In the case of a CyHV-3 infection, reduced type I IFN responses could be related to the potential ability of the virus to interfere with cellular sensing of foreign nucleic acids. Taken together, the results broaden our understanding of how common carp from different genetic lines interact with various viral pathogens

Gene expression analysis of common carp (Cyprinus carpio L.) lines during Cyprinid herpesvirus 3 infection yields insights into differential immune responses

Peer reviewe

Multi-length scale 5D diffraction imaging of Ni-Pd/CeO2-ZrO2/Al2O3 catalyst during partial oxidation of methane

A 5D diffraction imaging experiment (with 3D spatial, 1D time/imposed operating conditions and 1D scattering signal) was performed with a Ni–Pd/CeO2–ZrO2/Al2O3 catalyst. The catalyst was investigated during both activation and partial oxidation of methane (POX). The spatio-temporal resolved diffraction data allowed us to obtain unprecedented insight into the behaviour and fate of the various metal and metal oxide species and how this is affected by the heterogeneity across catalyst particles. We show firstly, how Pd promotion although facilitating Ni reduction, over time leads to formation of unstable Ni–Pd metallic alloy, rendering the impact of Pd beyond the initial reduction less important. Furthermore, in the core of the particles, where the metallic Ni is primarily supported on Al2O3, poor resistance towards coke deposition was observed. We identified that this preceded via the formation of an active yet metastable interstitial solid solution of Ni–C and led to the exclusive formation of graphitic carbon, the only polymorph of coke observed. In contrast, at the outermost part of the catalyst particle, where Ni is predominantly supported on CeO2–ZrO2, the graphite formation was mitigated but sintering of Ni crystallites was more severe

Multiscale investigation of adsorption properties of novel 3D printed UTSA-16 structures

Structuring MOF materials is a fundamental step towards their commercialization. Herein we report intensive characterization of 3D-printed UTSA-16 monoliths, facilitated by the development of a new non-aqueous ink formulation, employing hydroxypropyl cellulose and boehmite to adjust the rheology of the ink. What makes this formulation and printing process different from the printed adsorbents and catalysts published previously, is that the resulting structures in this work were not sintered. The presence of the binder matrix not only produced the physical properties for printability but also ensured a homogeneous dispersion of UTSA-16 in the structures, as well as gas adsorption characteristics. The monoliths were tested for the adsorption of different gases (N2, CH4, CO2 and H2O) in order to apply them into separation processes that contribute to defossilizing energy and fuels production. Water is strongly adsorbed in this material (~14 mol/kg at 293 K) and is competing with CO2 for adsorption sites. Breakthrough curves showed that the retention time of CO2 decreases significantly when the feed stream is saturated with water. In this study, synchrotron XRD-CT data were collected in situ, in a non-destructive way, and phase distribution maps were reconstructed to, for the first time, gain insight into the spatial and temporal evolution of the UTSA-16 containing phases in the operating 3D printed monolith during the exposure to CO2.publishedVersio

A scalable neural network architecture for self-supervised tomographic image reconstruction

We present a lightweight and scalable artificial neural network architecture which is used to reconstruct a tomographic image from a given sinogram. A self-supervised learning approach is used where the network iteratively generates an image that is then converted into a sinogram using the Radon transform; this new sinogram is then compared with the sinogram from the experimental dataset using a combined mean absolute error and structural similarity index measure loss function to update the weights of the network accordingly. We demonstrate that the network is able to reconstruct images that are larger than 1024 × 1024. Furthermore, it is shown that the new network is able to reconstruct images of higher quality than conventional reconstruction algorithms, such as the filtered back projection and iterative algorithms (SART, SIRT, CGLS), when sinograms with angular undersampling are used. The network is tested with simulated data as well as experimental synchrotron X-ray micro-tomography and X-ray diffraction computed tomography data